Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Own 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to rock/indie music 
Devices used daily: Smartphone;Smartwatch;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Nearly every day
LLMs used: Perplexity;Pi;ChatGPT;Other Deepseek
LLM use cases: Brainstorming;Generic chatbot conversation;Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Summarizing long texts 
Contexts of LLM use: Technical;Personal;Work 
Prompt 1: What was a dedicated device that was just made meant for running a local AI similar to a raspberry pi device but more powerful
Prompt 2: Which of those offers the best cost to performance ratio?
Prompt 3: What would be best to run a LLM like yourself locally?
Prompt 4: What linux should I main? mint, fedora, or debian
Prompt 5: How stable is debian testing?
Prompt 6: I feel like it doesn't offer anything I couldn't do my self to Fedora KDE spin
Prompt 7: You appear to be partial to Fedora, can't say I blame you
Prompt 8: What should I make sure to do for my uses after I install fedora 41?
Prompt 9: Can you edit those commands for someone with a 6700xt amd and a 17 12900 cpu, and explain what bad and dirty are in codecs?
Prompt 10: All these tweaks are relevant for fedora 41 correct?